3/2019 - 5 |
Dynamic Heart Rate Measurements from Video Sequences using Canonical Component AnalysisLING, S.-S. , PARAMESRAN, R. , YU, Y.-P. |
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Author keywords
video signal processing, image processing, image analysis, independent component analysis, blind source separation
References keywords
rate(7), heart(7), biomedical(7), optics(6), video(5)
Blue keywords are present in both the references section and the paper title.
About this article
Date of Publication: 2019-08-31
Volume 19, Issue 3, Year 2019, On page(s): 41 - 48
ISSN: 1582-7445, e-ISSN: 1844-7600
Digital Object Identifier: 10.4316/AECE.2019.03005
Web of Science Accession Number: 000486574100005
SCOPUS ID: 85072202782
Abstract
Dynamic heart rate computation from facial images obtained from video sequences has random artifacts and noises. A novel method is formulated by assuming that two video durations will contain the heart rate signals that are strongly correlated to each other while the random artifacts and noises are not correlated to each other. Canonical Component Analysis (CCA) is used to recover the heart-rate signals by determining the maximum correlation of the two video durations. The identified heart signal is then passed to a bandpass filter (0.8 - 4Hz) followed by Fast Fourier Transform to obtain the heart rate. Two experiments related to increasing and decreasing heart rate variations are carried out to determine the effectiveness of the proposed method. Eight subjects participated in each experiment, where their facial images were captured for a minute while they were cycling. Their heart rates varied from 83 to 153 beats per minute (BPM). The results of the proposed method are compared to a method using independent component analysis (ICA). The root mean square errors (RMSE) for the proposed method and ICA based-method that used 5-second video duration for the first and second experiments are 3.70 BPM and 2.33 BPM and 14.36 BPM and 9.72 BPM, respectively. |
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[1] The Determination of Absorption and Reduced Scattering Coefficients of Optical Phantoms Using a Frequency-Domain Multi-Distance Method in a Non-contact Manner, BAL, U., UTZINGER, U., BAL, A., MORAL, O. T., Advances in Electrical and Computer Engineering, ISSN 1582-7445, Issue 2, Volume 20, 2020.
Digital Object Identifier: 10.4316/AECE.2020.02001 [CrossRef] [Full text]
[2] Is Continuous Heart Rate Monitoring of Livestock a Dream or Is It Realistic? A Review, Nie, Luwei, Berckmans, Daniel, Wang, Chaoyuan, Li, Baoming, Sensors, ISSN 1424-8220, Issue 8, Volume 20, 2020.
Digital Object Identifier: 10.3390/s20082291 [CrossRef]
[3] Heart rate measurement and blur image quality metric via image processing: An overview, Paramesran, Raveendran, Hassan, Mohd Fikree, FIRST INTERNATIONAL CONFERENCE ON COMPUTATIONAL SCIENCE & DATA ANALYTICS: Incorporating the 1st South-East Asia Workshop on Computational Physics and Data Analytics (CPDAS 2021), ISBN , Issue , 2023.
Digital Object Identifier: 10.1063/5.0140251 [CrossRef]
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Faculty of Electrical Engineering and Computer Science
Stefan cel Mare University of Suceava, Romania
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